The bar chart illustrates the distribution of child mortality rates across five East African countries in 2019, expressed as percentages.
The chart highlights disparities in child mortality within the region, with Burundi and Tanzania experiencing the highest rates. These variations suggest differences in healthcare access, maternal health services, and socio-economic factors. Addressing child mortality requires targeted interventions, improved healthcare infrastructure, and policies to enhance child survival in the most affected countries.

Analysis of the Relationship The scatter plot illustrates the relationship between average daily income in 2019 and child mortality rate in 2020 across different countries. Key observations: 1. Negative Correlation – Higher daily income in 2019 is associated with lower child mortality in 2020. 2. Clustered Data – Countries with lower incomes (left side of the graph) have a higher variation in child mortality rates, while wealthier countries (right side) show consistently low mortality rates. 3. Non-Linear Trend – A sharp drop in child mortality occurs at relatively low income levels, suggesting that even modest income increases significantly impact child survival. 4. Outliers – Some countries with very low daily income have exceptionally high child mortality rates, indicating extreme vulnerability. Recommendations 🔹 Target Low-Income Countries – Prioritize investments in healthcare and social programs for nations with the lowest income levels. 🔹 Improve Healthcare Access – Strengthen maternal and child health services, especially in economically weaker regions. 🔹 Promote Economic Growth – Encourage income-generating activities, microfinance, and employment opportunities to lift families out of poverty. 🔹 Intervene Early – Provide direct child survival interventions (e.g., vaccination, nutrition programs) in the most affected areas. 🔹 Monitor Outliers – Investigate countries with extremely high child mortality rates to identify specific barriers to healthcare and economic development. Would you like a deeper statistical analysis or policy recommendations?